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12 pages, 3001 KiB  
Article
Melatonin Receptors and Serotonin: Age-Related Changes in the Ovaries
by Victoria Polyakova, Dmitrii Medvedev, Natalia Linkova, Mikhail Mushkin, Alexander Muraviev, Alexander Krasichkov, Anastasiia Dyatlova, Yanina Ivanova, Giuseppe Gullo and Anna Andreevna Gorelova
J. Pers. Med. 2024, 14(9), 1009; https://doi.org/10.3390/jpm14091009 - 22 Sep 2024
Viewed by 413
Abstract
Introduction. Melatonin and serotonin can influence certain aging processes in the ovaries. The main melatonin receptors are represented by types MT1 and MT2. The goal of investigation. Here, we evaluated the expression of genes and synthesis of MT1 and MT2 receptors, as well [...] Read more.
Introduction. Melatonin and serotonin can influence certain aging processes in the ovaries. The main melatonin receptors are represented by types MT1 and MT2. The goal of investigation. Here, we evaluated the expression of genes and synthesis of MT1 and MT2 receptors, as well as serotonin synthesis in the ovaries during ontogenesis. Methods. We analyzed histological material obtained from the ovaries of infants, women of younger and older reproductive age, premenopausal, menopausal, and postmenopausal women. For the analysis of MT1 and MT2 receptors and serotonin expression and synthesis, RT-PCR and immunohistochemistry were used. Results. We found that the synthesis of serotonin, as well as MT1 and MT2 receptors in the ovaries significantly decrease in ontogenesis. The sharpest drop in these molecules was observed in samples obtained from one-year-old infants, as well as from pubescent girls and menopausal women. A statistically significant 2.3–7.6-fold decrease in the expression of MTNR1A and MTNR1B genes in the ovaries was also observed in one-year-old infants, in adolescents, and in middle-aged women. Conclusions. These data are crucial to understanding the fundamental mechanisms of aging of the female reproductive system and the search for molecules predicting its aging. Full article
(This article belongs to the Section Sex, Gender and Hormone Based Medicine)
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Figure 1

Figure 1
<p>Dynamics of the expression area of MT1, MT2, and serotonin in ovarian tissue of women in different age groups.</p>
Full article ">Figure 2
<p>MT1 and MT2 expression (red staining) in human ovarian tissue of women in different age groups. Confocal microscopy (cell nuclei stained with Hoechst), magnification 200: (<b>a</b>) <span class="html-italic">MT1</span> and (<b>b</b>) <span class="html-italic">MT2</span>—children (1 y.o.); (<b>c</b>) <span class="html-italic">MT1</span> and (<b>d</b>) <span class="html-italic">MT2</span>—19–29 y.o.; (<b>e</b>) <span class="html-italic">MT1</span> and (<b>f</b>) <span class="html-italic">MT2</span>—60–74 y.o.</p>
Full article ">Figure 2 Cont.
<p>MT1 and MT2 expression (red staining) in human ovarian tissue of women in different age groups. Confocal microscopy (cell nuclei stained with Hoechst), magnification 200: (<b>a</b>) <span class="html-italic">MT1</span> and (<b>b</b>) <span class="html-italic">MT2</span>—children (1 y.o.); (<b>c</b>) <span class="html-italic">MT1</span> and (<b>d</b>) <span class="html-italic">MT2</span>—19–29 y.o.; (<b>e</b>) <span class="html-italic">MT1</span> and (<b>f</b>) <span class="html-italic">MT2</span>—60–74 y.o.</p>
Full article ">Figure 3
<p>Relative mRNA expression (c.u.) of <span class="html-italic">MTNR1A</span> and <span class="html-italic">MTNR1B</span> genes and serotonin in ovarian tissue of women in different age groups. (<b>a</b>) <span class="html-italic">MT1—MTNR1A</span>; (<b>b</b>) <span class="html-italic">MT2—MTNR1B.</span> Data are presented as a mean and standard deviation. * <span class="html-italic">p</span> &lt; 0.05 compared to the “Antenatal (&lt;1)” group; ** <span class="html-italic">p</span> &lt; 0.05 compared to the “1 y.o.” group; # <span class="html-italic">p</span> &lt; 0.05 compared to the “19–29 y.o.” group.</p>
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17 pages, 3972 KiB  
Article
Melatonin Receptor Expression in Primary Uveal Melanoma
by Anna Hagström, Ruba Kal Omar, Hans Witzenhausen, Emma Lardner, Oran Abdiu and Gustav Stålhammar
Int. J. Mol. Sci. 2024, 25(16), 8711; https://doi.org/10.3390/ijms25168711 - 9 Aug 2024
Viewed by 766
Abstract
Melatonin, noted for its anti-cancer properties in various malignancies, including cutaneous melanoma, shows promise in Uveal melanoma (UM) treatment. This study aimed to evaluate melatonin receptor expression in primary UM and its association with UM-related mortality and prognostic factors. Immunohistochemical analysis of 47 [...] Read more.
Melatonin, noted for its anti-cancer properties in various malignancies, including cutaneous melanoma, shows promise in Uveal melanoma (UM) treatment. This study aimed to evaluate melatonin receptor expression in primary UM and its association with UM-related mortality and prognostic factors. Immunohistochemical analysis of 47 primary UM tissues showed low expression of melatonin receptor 1A (MTNR1A) and melatonin receptor 1B (MTNR1B), with MTNR1A significantly higher in patients who succumbed to UM. Analysis of TCGA data from 80 UM patients revealed RNA expression for MTNR1A, retinoic acid-related orphan receptor alpha (RORα), and N-ribosyldihydronicotinamide:quinone oxidoreductase (NQO2), but not MTNR1B or G protein-coupled receptor 50 (GPR50). Higher MTNR1A RNA levels were observed in patients with a BRCA1 Associated Protein 1 (BAP1) mutation, and higher NQO2 RNA levels were noted in patients with the epithelioid tumor cell type. However, Kaplan–Meier analysis did not show distinct survival probabilities based on receptor expression. This study concludes that UM clinical samples express melatonin receptors, suggesting a potential mechanism for melatonin’s anti-cancer effects. Despite finding higher MTNR1A expression in patients who died of UM, no survival differences were observed. Full article
(This article belongs to the Special Issue Translational Research in Ophthalmic Pathology)
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Figure 1

Figure 1
<p>Kaplan–Meier survival curves and scatter plots for MTNR1A expression. (<b>A</b>) Survival curve comparing incidence of UM-related death in patients from the TCGA cohort with an MTNR1A RNA expression of less than 1 TPM compared to 1 TPM or above (<span class="html-italic">p</span> = 0.20), <span class="html-italic">n</span> = 80. (<b>B</b>) Survival curve comparing incidence of UM-related death in patients from the TCGA cohort with an MTNR1A RNA expression less than or equal to and above the median value (<span class="html-italic">p</span> = 0.54), <span class="html-italic">n</span> = 80. (<b>C</b>) Survival curve comparing the incidence of UM-related death in patients with IHC staining optical densities below or equal to and above the median in the nucleus (<span class="html-italic">p</span> = 0.72), <span class="html-italic">n</span> = 46. (<b>D</b>) Survival curve comparing the incidence of UM-related death in patients with IHC staining optical densities below or equal to and above the median in the cytoplasm (<span class="html-italic">p</span> = 0.80), <span class="html-italic">n</span> = 46. (<b>E</b>) Scatter plot comparing MTNR1A RNA expression in patient tumors with disomy 3 or monosomy 3. (<b>F</b>) Scatter plot comparing MTNR1A RNA expression in patients with tumors of an epithelioid cell type compared to other cell types (spindle or mixed). (<b>G</b>) Scatter plot comparing MTNR1A RNA expression in patients with the BAP1 wild type or BAP1 mutation where levels were higher in patients with the BAP1 wildtype (<span class="html-italic">p</span> = 0.0012). (<b>H</b>) Scatter plot comparing MTNR1A OD in the nucleus of tumor cells for patients who did or did not die due to uveal melanoma. (<b>I</b>) Scatter plot comparing MTNR1A OD in the cytoplasm of tumor cells for patients who did or did not die due to uveal melanoma (<span class="html-italic">p</span> &lt; 0.0001). Colored fields on the Kaplan–Meier curves indicate 95% confidence intervals. ns = not significant. TCGA cohort, St Erik cohort.</p>
Full article ">Figure 2
<p>MTNR1A and MTNR1B receptors in the nucleus vs. cytoplasm. (<b>A</b>) The mean optical density (OD) for MTNR1A was significantly higher in the cytoplasm compared to the nucleus (<span class="html-italic">p</span> &lt; 0.0001, <span class="html-italic">n</span> = 46); (<b>B</b>) The mean optical density (OD) for MTNR1B was significantly higher in the cytoplasm compared to the nucleus (<span class="html-italic">p</span> &lt; 0.0001, <span class="html-italic">n</span> = 45).</p>
Full article ">Figure 3
<p>Kaplan–Meier survival curves and scatter plots for MTNR1B expression. (<b>A</b>) Survival curve comparing the incidence of UM-related death in those with MTNR1B OD levels in the nucleus below or equal to and above the median value (<span class="html-italic">p</span> = 0.98), <span class="html-italic">n</span> = 45. (<b>B</b>) Survival curve comparing incidence of UM-related death in those with MTNR1B OD levels in the cytoplasm below or equal to and above the median value (<span class="html-italic">p</span> = 0.34), <span class="html-italic">n</span> = 45. (<b>C</b>) Scatter plot comparing MTNR1B RNA expression in patient tumors with disomy 3 or monosomy 3. (<b>D</b>) Scatter plot comparing MTNR1B RNA expression in patients with tumors of an epithelioid cell type compared to other cell types (spindle or mixed). (<b>E</b>) Scatter plot comparing MTNR1B RNA expression in patients with the BAP1 wild type or BAP1 mutation. (<b>F</b>) Scatter plot comparing MTNR1B OD levels in the nucleus of tumor cells for patients who did or did not die due to uveal melanoma. (<b>G</b>) Scatter plot comparing MTNR1B OD levels in the cytoplasm of tumor cells for patients who did or did not die due to uveal melanoma. Colored fields on the Kaplan–Meier curves indicate 95% confidence intervals. ns = not significant. TCGA cohort, St Erik cohort.</p>
Full article ">Figure 4
<p>IHC data analysis. Using QuPath Bioimage analysis v. 0.4.1, mean DAB (3,3′-diaminobenzidine) staining intensity, measured by optical density (OD) for melatonin receptors were calculated from immunohistochemically stained primary uveal melanoma tissue. (<b>A</b>) Example of uveal melanoma tissue with positive staining where the presence of DAB (purple-red in color) signifies the presence of melatonin receptors. Cells which appear blue due to background hematoxylin staining, lack the presence of DAB and are therefore considered negative. (<b>B</b>) A closer view of stained tissue where positive (purple) and negative (blue) cells are visualized. (<b>C</b>) Calibration is performed by manually selecting a positive and negative cell. Note, the arrow to the left indicates a negative cell while the arrow to the right indicates a positive cell. (<b>D</b>) Three circular sections 500 μm in diameter are selected for analysis. (<b>E</b>) Positive Cell detection is performed to identify positive and negative cells within the selected sections. (<b>F</b>) A closer view of the detection of positive cells by QuPath. (<b>G</b>) An example of a false positive cell, indicated by an arrow, which is removed manually. (<b>H</b>) An example of the mean staining intensity for the entire selected area.</p>
Full article ">Figure A1
<p>Kaplan–Meier survival curve and scatter plots for NQO2 expression (TCGA cohort). (<b>A</b>) Survival curve comparing incidence of UM-related death in those with an NQO2 RNA expression above or below the median TPM value (<span class="html-italic">p</span> = 0.20), <span class="html-italic">n</span> = 80. (<b>B</b>) Scatter plot comparing NQO2 RNA expression in patient tumors with disomy 3 or monosomy 3. (<b>C</b>) Scatter plot comparing NQO2 RNA expression in patients with tumors of an epithelioid cell type compared to other cell types (<span class="html-italic">p</span> = 0.0124). (<b>D</b>) Scatter plot comparing NQO2 RNA expression in patients with the <span class="html-italic">BAP1</span> wild type or <span class="html-italic">BAP1</span> mutation. Colored fields on the Kaplan–Meier curve indicate 95% confidence intervals. ns = not significant.</p>
Full article ">Figure A2
<p>Kaplan–Meier survival curve and scatter plots for RORα expression (TCGA cohort). (<b>A</b>) Survival curve comparing incidence of UM-related death in those with RORα RNA expression above or below 1 TPM (transcripts per million) (<span class="html-italic">p</span> = 0.20), <span class="html-italic">n</span> = 80. (<b>B</b>) Survival curve comparing incidence of UM-related death in those with RORα RNA expression above or below the median value (<span class="html-italic">p</span> = 0.97), <span class="html-italic">n</span> = 80. (<b>C</b>) Scatter plot comparing RORα RNA expression in patient tumors with disomy 3 or monosomy 3. (<b>D</b>) Scatter plot comparing RORα RNA expression in patients with tumors of an epithelioid cell type compared to other cell types (spindle or mixed). (<b>E</b>) Scatter plot comparing RORα RNA expression in patients with the <span class="html-italic">BAP1</span> wild type or <span class="html-italic">BAP1</span> mutation. Colored fields on the Kaplan–Meier curve indicate 95% confidence intervals. ns = not significant.</p>
Full article ">Figure A3
<p>Scatter plots for GPR50 expression (TCGA cohort). (<b>A</b>) Scatter plot comparing GPR50 RNA expression in patient tumors with disomy 3 or monosomy 3. (<b>B</b>) Scatter plot comparing GPR50 RNA expression in patients with tumors of an epithelioid cell type compared to other cell types. (<b>C</b>) Scatter plot comparing GPR50 RNA expression in patients with the <span class="html-italic">BAP1</span> wild type or <span class="html-italic">BAP1</span> mutation. ns = not significant.</p>
Full article ">
3 pages, 143 KiB  
Proceeding Paper
The Association of MTNR1A Gene Alleles with the Response to Estrus Induction Treatments in Improved and Non-Improved Greek Indigenous Sheep Breeds
by Danai Antonopoulou, Ioannis A. Giantsis, George K. Symeon and Melpomeni Avdi
Proceedings 2024, 94(1), 3; https://doi.org/10.3390/proceedings2024094003 - 19 Jan 2024
Viewed by 639
Abstract
Seasonality in sheep reproduction and related limitations make milk production challenging throughout the year. In the present study, we investigated the response to estrus induction treatments in three indigenous breeds, Florina, Chios, and Karagouniko, as well as the melatonin receptor 1A gene variants [...] Read more.
Seasonality in sheep reproduction and related limitations make milk production challenging throughout the year. In the present study, we investigated the response to estrus induction treatments in three indigenous breeds, Florina, Chios, and Karagouniko, as well as the melatonin receptor 1A gene variants in relation to this response. The three distinct synchronization methods were A: intravaginal sponges, B: GNRH use, and C: male effect. In group A, fertility was 85%, and Florina ewes expressed estrus at 90% in July. Ewes from Karagouniko and Chios had fecundity rates of 95% and 99%, respectively, and 100% estrus expression. The Florina ewes in group B expressed estrus at a percentage of 60%, with a fecundity rate of 57%, the Karagouniko ewes at a percentage of 65%, with a fecundity rate of 54%, and the Chios breed animals at a percentage of 87%, with a fecundity rate of 85%. Twenty to twenty-five days after ram induction, 68% of the Florina breed in group C showed signs of estrus, compared to 84% and 94% of Karagouniko and Chios breeds, respectively. In both Florina and Karagouniko breeds, all treatments showed a substantial difference in the frequency of the four identified SNPs in the MTNR1A gene between ewes who expressed estrus and ewes who did not. The genetic improvement based on the alleles analyzed in the current study is expected to decrease seasonality rates in indigenous sheep breeds. Full article
20 pages, 6529 KiB  
Article
Melatonin Alleviates Lipopolysaccharide-Induced Abnormal Pregnancy through MTNR1B Regulation of m6A
by Shisu Zhao, Yanjun Dong, Yuanyuan Li, Zixu Wang, Yaoxing Chen and Yulan Dong
Int. J. Mol. Sci. 2024, 25(2), 733; https://doi.org/10.3390/ijms25020733 - 5 Jan 2024
Cited by 1 | Viewed by 1595
Abstract
Pregnancy is a highly intricate and delicate process, where inflammation during early stages may lead to pregnancy loss or defective implantation. Melatonin, primarily produced by the pineal gland, exerts several pharmacological effects. N6-methyladenosine (m6A) is the most prevalent mRNA modification in eukaryotes. This [...] Read more.
Pregnancy is a highly intricate and delicate process, where inflammation during early stages may lead to pregnancy loss or defective implantation. Melatonin, primarily produced by the pineal gland, exerts several pharmacological effects. N6-methyladenosine (m6A) is the most prevalent mRNA modification in eukaryotes. This study aimed to investigate the association between melatonin and m6A during pregnancy and elucidate the underlying protective mechanism of melatonin. Melatonin was found to alleviate lipopolysaccharide (LPS)-induced reductions in the number of implantation sites. Additionally, it mitigated the activation of inflammation, autophagy, and apoptosis pathways, thereby protecting the pregnancy process in mice. The study also revealed that melatonin regulates uterine m6A methylation levels and counteracts abnormal changes in m6A modification of various genes following LPS stimulation. Furthermore, melatonin was shown to regulate m6A methylation through melatonin receptor 1B (MTNR1B) and subsequently modulate inflammation, autophagy, and apoptosis through m6A. In conclusion, our study demonstrates that melatonin protects pregnancy by influencing inflammation, autophagy, and apoptosis pathways in an m6A-dependent manner via MTNR1B. These findings provide valuable insights into the mechanisms underlying melatonin’s protective effects during pregnancy and may have implications for potential therapeutic strategies in managing pregnancy-related complications. Full article
(This article belongs to the Section Biochemistry)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The protective effect of melatonin on mouse embryo implantation. (<b>A</b>) Schematic diagram of the animal experimental design. (<b>B</b>) Changes in the body weight, water consumption, and daily feed intake of pregnant mice. <span class="html-italic">n</span> = 36 independent biological replicates. (<b>C</b>) Implantation sites were indicated by injecting Chicago Sky Blue dye. (<b>D</b>) The number of implantation sites in mice. <span class="html-italic">n</span> = 15 independent biological replicates. (<b>E</b>) The weight of uterus in mice. <span class="html-italic">n</span> = 15 independent biological replicates. (<b>F</b>) The blood glucose values in mice. <span class="html-italic">n</span> = 15 independent biological replicates. (<b>G</b>) Blood was analyzed for the number of RBC, HB, PLT, WBC. RBC: red blood cell; HB: hemoglobin concentration; PLT: platelet count; white blood cell. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>H</b>) Serum hormone analysis in mice. <span class="html-italic">n</span> = 3 independent biological replicates. P4: progesterone; E2: Estradiol-17β; CORT: corticosterone; NOR: noradrenaline. Veh: vehicle treatment group; LPS: LPS treatment group; Mel+LPS: melatonin and LPS co-treatment group; Mel: melatonin treatment group; The data are presented as the mean ± SD. Levels of statistical significance for all data were determined by one-way ANOVA and Tukey’s test (* Indicates significant difference between the two groups; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 2
<p>Melatonin alleviates LPS-induced inflammation, autophagy, and apoptosis in uterus. (<b>A</b>) Gene Ontology (GO) enrichment analyses of DEGs between Con and Lps. (<b>B</b>) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs between Con and Lps. The top 21 pathways enriched in KEGG. (<b>C</b>) Uterus cytokine analysis by Luminex. <span class="html-italic">n</span> = 4 independent biological replicates. (<b>D</b>) Violin plots show the expression levels inflammation-related genes mRNAs between Con and Lps. (<b>E</b>) Violin plots show the expression levels autophagy-related genes mRNAs between Con and Lps. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>F</b>) Violin plots show the expression levels apoptosis-related genes mRNAs between Con and Lps. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>G</b>) The mRNA levels of the inflammation-related genes in uterus of mice. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>H</b>) The mRNA levels of the autophagy-related genes in uterus of mice. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>I</b>) The mRNA levels of the apoptosis-related genes in uterus of mice. <span class="html-italic">n</span> = 3 independent biological replicates. Veh: vehicle treatment group; LPS: LPS treatment group; Mel+LPS: melatonin and LPS co-treatment group; Mel: melatonin treatment group; The data are presented as the mean ± SD. Levels of statistical significance for all data were determined by one-way ANOVA and Tukey’s test (* Indicates significant difference between the two groups; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 3
<p>Melatonin alleviates LPS-induced elevated m6A levels in uterus. (<b>A</b>) Violin plots show the expression levels of m6A regulaters mRNAs between Con and Lps. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>B</b>) Global m6A levels in the uterus. <span class="html-italic">n</span> = 6 independent biological replicates. (<b>C</b>) The mRNA levels of m6A regulaters in the uterus of mice. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>D</b>) Western blot bands of METTL3 and FTO. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>E</b>) Protein–protein interaction (PPI) network of the significant genes. Using the STRING online database. (<b>F</b>) The mRNA levels of <span class="html-italic">Mtnr1b</span> in the uterus of mice. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>G</b>) Immunohistochemical (IHC) staining of METTL3 and FTO in the uterus on D5. <span class="html-italic">n</span> = 3 independent biological replicates. S: stroma; LE: luminal epithelium; GE: glandular epithelium; Myo: myometrium. Veh: vehicle treatment group; LPS: LPS treatment group; Mel+LPS: melatonin and LPS co-treatment group; Mel: Melatonin treatment group; The data are presented as the mean ± SD. Levels of statistical significance for all data were determined by one-way ANOVA and Tukey’s test (* Indicates significant difference between the two groups; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 4
<p>m6A-seq analysis of m6A modification after melatonin and LPS stimulation. (<b>A</b>) The annotation of m6A-seq different reads between different treatments. (<b>B</b>) Genome browser view of m6A-seq different reads between different treatments. (<b>C</b>) The motif of m6A-seq different reads between different treatments. (<b>D</b>) Violin plots of the m6A-up and m6A-down genes between different treatments. (<b>E</b>) KEGG pathway enrichment of m6A-up genes between LPS group and Veh group. (<b>F</b>) GO enrichment of m6A-up genes between LPS group and Veh group. (<b>G</b>) Venn diagram of m6A-up genes in the LPS group and m6A-down genes in the Mel+LPS group. (<b>H</b>) Venn diagram of m6A-down genes in the LPS group and m6A-up genes in the Mel+LPS group. <span class="html-italic">n</span> = 3 independent biological replicates. Veh: vehicle treatment group; LPS: LPS treatment group; Mel+LPS: melatonin and LPS co-treatment group.</p>
Full article ">Figure 5
<p>Melatonin alleviates LPS-induced inflammation, autophagy, and apoptosis in human endometrial stromal cells. (<b>A</b>) Cell proliferation assay by CCK8 method. <span class="html-italic">n</span> = 6 independent biological replicates. LPS: added LPS only; Mel+LPS: added melatonin and LPS; * Indicates a significant difference compared with the LPS 0 μg/mL group; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; <sup>#</sup> Indicates a significant difference compared with the LPS 50 μg/mL group; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05; <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>) Western blot bands of inflammation-related proteins in human endometrial stromal cells. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>C</b>) Western blot bands of autophagy related proteins in human endometrial stromal cells. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>D</b>) Western blot bands of apoptosis related proteins in human endometrial stromal cells. <span class="html-italic">n</span> = 3 independent biological replicates. Veh: vehicle treatment group; LPS: LPS treatment group; Mel+LPS: melatonin and LPS co-treatment group; Mel: melatonin treatment group; The data are presented as the mean ± SD. Levels of statistical significance for all data were determined by one-way ANOVA and Tukey’s test (* Indicates significant difference between the two groups; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 6
<p>Melatonin alleviates LPS-induced elevated m6A levels in human endometrial stromal cells. (<b>A</b>) Global m6A levels of human endometrial stromal cells treated with LPS and different concentrations of melatonin. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>B</b>) The mRNA levels of the m6A regulators in uterus of human endometrial stromal cells treated with LPS and melatonin. <span class="html-italic">n</span> = 3 independent biological replicates. (<b>C</b>) Immunofluorescence of m6A-related proteins in HESCs. (<b>D</b>) Immunofluorescence of MTNR1B in HESCs. (<b>E</b>) The ratio of the fluorescence intensity of METTL3 in the nucleus to the fluorescence intensity of METTL3 in the whole cell. <span class="html-italic">n</span> = 6 independent biological replicates. (<b>F</b>) The ratio of the fluorescence intensity of FTO in the nucleus to the fluorescence intensity of FTO in the whole cell. <span class="html-italic">n</span> = 6 independent biological replicates. (<b>G</b>) The ratio of the fluorescence intensity of MTNR1B in the nucleus to the fluorescence intensity of MTNR1B in the whole cell. <span class="html-italic">n</span> = 6 independent biological replicates. (<b>H</b>) The mRNA levels of <span class="html-italic">MTNR1B</span> in the uterus of mice. The experiments were performed in triplicate. The data are presented as the mean ± SD. Levels of statistical significance for all data were determined by one-way ANOVA and Tukey’s test (* Indicates significant difference between the two groups; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 7
<p>Melatonin plays a protective role through MTNR1B. (<b>A</b>) Cell proliferation assay by CCK8 method. <span class="html-italic">n</span> = 6 independent biological replicates. 4-P-PDOT: 4-phenyl-2-propionamidotetralin; SAH: S-adenosylhomocysteine; * Indicates a significant difference compared with the 4-P-PDOT/SAH 0 μM group; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; <sup>#</sup> Indicates a significant difference compared with the LPS added group alone Difference; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05; <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01; <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) Global m6A levels of human endometrial stromal cells treated with 4PPDOT. (<b>C</b>) Western blot bands of inflammation-related proteins in human endometrial stromal cells. (<b>D</b>) Immunoblot analysis of <span class="html-italic">p</span>-RELA, RELA, ERK1/2. (<b>E</b>) Western blot bands of autophagy related proteins in human endometrial stromal cells. (<b>F</b>) Immunoblot analysis of LC3B, ATG5, ATG7. (<b>G</b>) Western blot bands of apoptosis related proteins in human endometrial stromal cells. (<b>H</b>) Immunoblot analysis of c-PARP, BAX, CASP1, c-CASP3. (<b>I</b>) Flow cytometry was used to detect apoptosis after adding the 4PPDOT and melatonin, and apoptosis cells were measured. <span class="html-italic">n</span> = 3 independent biological replicates. Veh: vehicle treatment group; LPS: LPS treatment group; Mel+LPS: melatonin and LPS co-treatment group; Mel: melatonin treatment group; The data are presented as the mean ± SD. Levels of statistical significance for all data were determined by one-way ANOVA and Tukey’s test (* Indicates significant difference between the two groups; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The mechanism by which melatonin protects pregnancy.</p>
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21 pages, 3566 KiB  
Article
Blue Light and Temperature Actigraphy Measures Predicting Metabolic Health Are Linked to Melatonin Receptor Polymorphism
by Denis Gubin, Konstantin Danilenko, Oliver Stefani, Sergey Kolomeichuk, Alexander Markov, Ivan Petrov, Kirill Voronin, Marina Mezhakova, Mikhail Borisenkov, Aislu Shigabaeva, Natalya Yuzhakova, Svetlana Lobkina, Dietmar Weinert and Germaine Cornelissen
Biology 2024, 13(1), 22; https://doi.org/10.3390/biology13010022 - 30 Dec 2023
Cited by 3 | Viewed by 3439
Abstract
This study explores the relationship between the light features of the Arctic spring equinox and circadian rhythms, sleep and metabolic health. Residents (N = 62) provided week-long actigraphy measures, including light exposure, which were related to body mass index (BMI), leptin and cortisol. [...] Read more.
This study explores the relationship between the light features of the Arctic spring equinox and circadian rhythms, sleep and metabolic health. Residents (N = 62) provided week-long actigraphy measures, including light exposure, which were related to body mass index (BMI), leptin and cortisol. Lower wrist temperature (wT) and higher evening blue light exposure (BLE), expressed as a novel index, the nocturnal excess index (NEIbl), were the most sensitive actigraphy measures associated with BMI. A higher BMI was linked to nocturnal BLE within distinct time windows. These associations were present specifically in carriers of the MTNR1B rs10830963 G-allele. A larger wake-after-sleep onset (WASO), smaller 24 h amplitude and earlier phase of the activity rhythm were associated with higher leptin. Higher cortisol was associated with an earlier M10 onset of BLE and with our other novel index, the Daylight Deficit Index of blue light, DDIbl. We also found sex-, age- and population-dependent differences in the parametric and non-parametric indices of BLE, wT and physical activity, while there were no differences in any sleep characteristics. Overall, this study determined sensitive actigraphy markers of light exposure and wT predictive of metabolic health and showed that these markers are linked to melatonin receptor polymorphism. Full article
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<p>Twenty-four-hour patterns of blue light exposure in the Arctic by seasons. (<b>A</b>,<b>B</b>) Mean blue light exposure during four seasons (spring equinox, autumn equinox, winter polar night, summer polar day) in Arctic residents. (<b>C</b>) Mean values of blue light exposure for consecutive 30 min epochs during spring equinox (blue line) against reference curve of optimal light exposure (red line). Vertical bars denote 95% confidence intervals. Reference curve for optimal blue light exposure is dashed brown line. (<b>D</b>) log<sub>10</sub>-transformed values of blue light exposure for consecutive 30 min epochs during spring equinox (blue line) against log<sub>10</sub>-transformed reference curve of the optimal light exposure (red line).</p>
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<p>Subtle differences in nocturnal blue light exposure challenge metabolic health in the Arctic spring. (<b>A</b>) Distinct 30 min time windows of blue light exposure in Arctic residents with different body mass index (BMI) values. Twenty-four-hour patterns of blue light exposure, expressed as log<sub>10</sub> in normal weight (BMI &lt; 25); overweight (BMI = 25–30) and obese (BMI &gt; 30) individuals are depicted. Vertical bars denote 95% confidence intervals. Green lines BMI &lt;25; red lines BMI &gt;25; black lines BMI &gt;30 ● <span class="html-italic">p</span> &lt; 0.1 (22:00–22:30; 00:30–01:00); * <span class="html-italic">p</span> &lt; 0.05 (21:00–22:00); ** <span class="html-italic">p</span> &lt; 0.01 (23:00–00:30; 02:00–02:30) for mean-rank differences between BMI &lt; 25 and 25–30; # <span class="html-italic">p</span> &lt; 0.05 (23:00–23:30 and 02:00–02:30) for mean-rank differences between BMI = 25–30 and &gt;30. Note higher exposure to blue light in the evening and early night among overweight and obese compared to lean participants. (<b>B</b>) Chart of r-values from linear regression of BMI with respect to blue light exposure (ordinate) in consecutive 30 min time windows (abscissa) (blue curve). Horizontal light blue line corresponds to the threshold of significance at <span class="html-italic">p</span> &lt; 0.05; dark-blue horizontal line: threshold of significance after Benjamini–Hochberg’s correction for multiple testing at 0.1. Red curve: cosinor model rejects zero-amplitude assumption of no rhythmicity (<span class="html-italic">p</span> = 0.002), acrophase = 23:24.</p>
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<p>MTNR1B rs10830963 G-allele defines the association between body mass index (BMI) and wrist temperature (wT) MESOR. (<b>A</b>,<b>B</b>) Lower wT MESOR is associated with BMI in G-allele carriers but not in those with the CC genotype. Strength of correlation between wT MESOR and BMI is significantly stronger in MTNR1B G-allele carriers ((<b>A</b>), r = −0.659; <span class="html-italic">p</span> = 0.0009, n = 22) than in those with the CC genotype ((<b>B</b>), r = 0.049; <span class="html-italic">p</span> = 0.803, n = 28); z = −2.825, <span class="html-italic">p</span> = 0.005. (<b>C</b>,<b>D</b>) Twenty-four-hour patterns show lower wT, particularly in the morning, in overweight G-allele carriers than in normal-weight G-allele carriers (<b>C</b>); this difference is absent in those with the CC genotype (<b>D</b>). Vertical bars denote 95% confidence intervals. blue BMI &lt; 25; red BMI &gt; 25.</p>
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<p>Association between higher nocturnal blue light exposure and higher body mass index (BMI) is linked to the MTNR1B rs10830963 G-allele. (<b>A</b>,<b>B</b>) ANOVA for Time*group interaction, blue light exposure log<sub>10</sub> in MTNR1B G-allele carriers (<b>A</b>), F<sub>(47, 1584)</sub> = 1.982, <span class="html-italic">p</span> = 0.0001; in those with the MTNR1B CC genotype (<b>B</b>), F<sub>(47, 1248)</sub> =1.383, <span class="html-italic">p</span> = 0.046. Time * BMI * MTNR1B interaction for blue light exposure log<sub>10</sub> is significant, F<sub>(47, 2832)</sub> =1.504, <span class="html-italic">p</span> = 0.015. Thirty-minute time windows of normalized wrist temperature and activity in Arctic residents with different BMIs. Vertical bars denote 95% confidence intervals. (<b>C</b>,<b>D</b>) Chart of r-values from a linear regression of BMI with blue light exposure (ordinate) in consecutive 30 min time windows (abscissa) (blue curve). (<b>C</b>) G-allele carriers; (<b>D</b>) CC genotype (non-carriers). Horizontal light blue line corresponds to the threshold of significance at <span class="html-italic">p</span> &lt; 0.05; dark-blue horizontal line corresponds to the threshold of significance after Benjamini–Hochberg’s correction for multiple testing at 0.1. Thresholds are similar for G-allele carriers. Red curve: cosinor model rejects zero-amplitude assumption of no rhythmicity; <span class="html-italic">p</span> &lt; 0.00001, acrophase = 01:41 for G-allele carriers, CG + GG genotypes; <span class="html-italic">p</span> = 0.0002; acrophase = 17:15 for CC genotype. Correlation of the higher evening blue light exposure with the higher BMI after correction for multiple testing is significant in G-allele carriers during time epochs shaded in blue.</p>
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18 pages, 13597 KiB  
Article
Melatonin-Mediated Suppression of mtROS-JNK-FOXO1 Pathway Alleviates Hypoxia-Induced Apoptosis in Porcine Granulosa Cells
by Xuan Zhang, Dingding Zhang, Hongmin Li, Zhaojun Liu, Yatong Yang, Jiameng Li, Lishiyuan Tang, Jingli Tao, Honglin Liu and Ming Shen
Antioxidants 2023, 12(10), 1881; https://doi.org/10.3390/antiox12101881 - 19 Oct 2023
Cited by 3 | Viewed by 1524
Abstract
Numerous studies have established that the hypoxic conditions within ovarian follicles induce apoptosis in granulosa cells (GCs), a pivotal hallmark of follicular atresia. Melatonin (N-acetyl-5-methoxytryptamine, MT), a versatile antioxidant naturally present in follicular fluid, acts as a safeguard for maintaining GCs’ survival during [...] Read more.
Numerous studies have established that the hypoxic conditions within ovarian follicles induce apoptosis in granulosa cells (GCs), a pivotal hallmark of follicular atresia. Melatonin (N-acetyl-5-methoxytryptamine, MT), a versatile antioxidant naturally present in follicular fluid, acts as a safeguard for maintaining GCs’ survival during stress exposure. In this study, we unveil an innovative protective mechanism of melatonin against hypoxia-triggered GC apoptosis by selectively inhibiting mitochondrial ROS (mtROS) generation. Specifically, under hypoxic conditions, a gradual accumulation of mitochondrial ROS occurred, consequently activating the JNK-FOXO1 pathway, and driving GCs toward apoptosis. The blocking of JNK or FOXO1 diminished hypoxia-induced GC apoptosis, but this effect was nullified in the presence of GSH, indicating that mtROS instigates apoptosis through the JNK-FOXO1 pathway. Consistent with this, hypoxic GCs treated with melatonin exhibited decreased levels of mtROS, reduced JNK-FOXO1 activation, and mitigated apoptosis. However, the protective capabilities of melatonin were attenuated upon inhibiting its receptor MTNR1B, accompanied by the decreased expression of antioxidant genes. Notably, SOD2, a key mitochondrial antioxidant gene modulated by the melatonin–MTNR1B axis, effectively inhibited the activation of mtROS-JNK-FOXO1 and subsequent apoptosis, whereas SOD2 knockdown abrogated the protective role of melatonin in hypoxic GCs. In conclusion, our study elucidates that melatonin, through MTNR1B activation, fosters SOD2 expression, effectively quelling mtROS-JNK-FOXO1-mediated apoptosis in follicular GCs under hypoxic stress. Full article
(This article belongs to the Special Issue Advances in Mitochondrial Redox Biology)
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Figure 1
<p>Hypoxia promotes apoptosis of GCs by increasing the accumulation of mtROS. (<b>A</b>) Summary of the experimental design. (<b>B</b>) Representative images display MitoSOX Red fluorescence and MitoTracker Green fluorescence. Scale bar = 20 μm. The ratio of MitoSOX to MitoTracker is presented on the right side. (<b>C</b>) Representative images of MitoSOX Red fluorescence and MitoTracker Green fluorescence. Scale bar = 20 μm. (<b>D</b>) Quantification of the fluorescence ratio of MitoSOX to MitoTracker. (<b>E</b>) After a 24 h treatment of GCs, TUNEL staining was utilized to indicate cells undergoing apoptosis. Scale bar = 50 μm. (<b>F</b>) Quantification of the ratio of TUNEL-positive staining cells. Data are presented as means ± S.E.M. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>Hypoxia induces GC apoptosis by activating the mtROS-JNK-FOXO1 pathway. (<b>A</b>) The levels of JNK, p-JNK, BAX, BCL2, and Cleaved-Caspase3 of GCs in each group were detected by Western blotting. (<b>B</b>) The protein levels were normalized with TUBA1A. (<b>C</b>) FOXO1 (red) nuclear localization was assessed using immunofluorescence, with the nucleus counterstained using DAPI (blue). Scale bar = 10 μm. Data are presented as means ± S.E.M. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.01 **.</p>
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<p>Blocking the JNK-FOXO1 pathway alleviates mtROS-induced GC apoptosis. (<b>A</b>) After pre-treating GCs with the JNK inhibitor SP600125 for 2 h, they were further treated with GSH or PBS for 12 h. Subsequently, the protein levels of JNK, p-JNK, and Cleaved-Caspase3 were assessed using Western blot, (<b>B</b>) followed by grayscale analysis. (<b>C</b>) After knocking down GCs using siRNA for 12 h, they were further treated with GSH or PBS for 12 h. Subsequently, the protein levels of FOXO1 and Cleaved-Caspase3 were assessed using Western blot, (<b>D</b>) followed by grayscale analysis. (<b>E</b>) After pre-treating GCs with the FOXO1 inhibitor AS1842856 for 2 h, they were further treated with GSH or PBS for 12 h. Subsequently, the protein levels of FOXO1 and Cleaved-Caspase3 were assessed using Western blot, (<b>F</b>) followed by grayscale analysis. Data are shown as mean ± SEM. ns, not significance, <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.01 **, <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>Blocking the JNK-FOXO1 pathway alleviates mtROS-induced GC apoptosis. (<b>A</b>) Representative images of MitoSOX Red fluorescence and MitoTracker Green fluorescence. Scale bar = 20 μm. (<b>B</b>) The ratio of MitoSOX/MitoTracker. (<b>C</b>) After a 24 h treatment of GCs, TUNEL staining was utilized to indicate cells undergoing apoptosis. Scale bar = 50 μm. (<b>D</b>) Quantification of the ratio of TUNEL-positive staining cells. Data are shown as means ± S.E.M. ns, not significance, <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.01 **, <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>Melatonin alleviates the accumulation of mtROS and inhibits JNK activation through the MTNR1B receptor in GCs. (<b>A</b>) Representative images of MitoSOX Red fluorescence and MitoTracker Green fluorescence. Scale bar = 20 μm. The ratio of MitoSOX to MitoTracker fluorescence is presented on the right side. (<b>B</b>) Quantification of antioxidant enzyme gene expression in GCs following treatment using qRT-PCR. (<b>C</b>) After pre-treating GCs with the MTNR1B inhibitor 4P PDOT for 2 h, they were further treated with MT or DMSO for 12 h. Subsequently, the protein levels of JNK, p-JNK, SOD2, and Cleaved-Caspase3 were assessed using Western blot. (<b>D</b>) The protein levels were normalized with TUBA1A. Data are shown as means ± S.E.M. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.01 **, <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>Melatonin inhibits hypoxia-induced nuclear translocation of FOXO1 and apoptosis through MTNR1B. (<b>A</b>) FOXO1 (red) nuclear localization was assessed using immunofluorescence, with the nucleus counterstained using DAPI (blue). Scale bar = 10 μm. (<b>B</b>) After a 24 h treatment of GCs, TUNEL staining was utilized to indicate cells undergoing apoptosis. Scale bar = 50 μm. (<b>C</b>) Quantification of the ratio of TUNEL-positive staining cells. Data are shown as means ± S.E.M. <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>Melatonin reduces the accumulation of mtROS through SOD2. (<b>A</b>) Overview of the experimental design. (<b>B</b>) Quantitative real-time PCR was employed to detect the transcription levels of the SOD2 gene after overexpression. (<b>C</b>) Quantitative real-time PCR was utilized to assess the transcription levels of the SOD2 gene following knockdown. (<b>D</b>) Representative images display MitoSOX Red fluorescence and MitoTracker Green fluorescence. Scale bar = 20 μm. The ratio of MitoSOX to MitoTracker fluorescence is presented on the right side. Data are shown as means ± S.E.M. <span class="html-italic">p</span> &lt; 0.01 **, <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>Melatonin alleviates hypoxia-induced mtROS-JNK-FOXO1 pathway activity and apoptosis through SOD2 in GCs. (<b>A</b>,<b>B</b>) Protein levels of JNK, p-JNK, SOD2, and Cleaved-Caspase3 were assessed using Western blotting, with protein levels normalized using TUBA1A. (<b>C</b>) FOXO1 (red) nuclear localization was assessed using immunofluorescence, with the nucleus counterstained using DAPI (blue). Scale bar = 10 μm. Data are shown as means ± S.E.M. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.01 **, <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>A schematic model depicts melatonin-mediated GC protection against hypoxic damage via activating the MTNR1B-SOD2-mtROS-JNK-FOXO1 axis. Under hypoxic conditions, decreased SOD2 levels and the accumulation of mitochondrial ROS contribute to the activation of the JNK-FOXO1 pathway, ultimately inducing GC apoptosis. In the presence of melatonin, it binds to the MTNR1B receptor and promotes SOD2 expression, facilitating the clearance of accumulated mtROS, thereby abrogating the activation of the JNK-FOXO1 pathway, and consequently inhibiting hypoxia-induced GCs apoptosis. Upregulation is represented by the thin red arrow, while downregulation is denoted by the thin blue arrow.</p>
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21 pages, 20855 KiB  
Article
Regulation of Adipose-Derived Stem Cell Activity by Melatonin Receptors in Terms of Viability and Osteogenic Differentiation
by Aleksandra Skubis-Sikora, Bartosz Sikora, Weronika Małysiak, Patrycja Wieczorek and Piotr Czekaj
Pharmaceuticals 2023, 16(9), 1236; https://doi.org/10.3390/ph16091236 - 1 Sep 2023
Cited by 1 | Viewed by 1216
Abstract
Melatonin is a hormone secreted mainly by the pineal gland and acts through the Mel1A and Mel1B receptors. Among other actions, melatonin significantly increases osteogenesis during bone regeneration. Human adipose-derived mesenchymal stem cells (ADSCs) are also known to have the potential to differentiate [...] Read more.
Melatonin is a hormone secreted mainly by the pineal gland and acts through the Mel1A and Mel1B receptors. Among other actions, melatonin significantly increases osteogenesis during bone regeneration. Human adipose-derived mesenchymal stem cells (ADSCs) are also known to have the potential to differentiate into osteoblast-like cells; however, inefficient culturing due to the loss of properties over time or low cell survival rates on scaffolds is a limitation. Improving the process of ADSC expansion in vitro is crucial for its further successful use in bone regeneration. This study aimed to assess the effect of melatonin on ADSC characteristics, including osteogenicity. We assessed ADSC viability at different melatonin concentrations as well as the effect on its receptor inhibitors (luzindole or 4-P-PDOT). Moreover, we analyzed the ADSC phenotype, apoptosis, cell cycle, and expression of MTNR1A and MTNR1B receptors, and its potential for osteogenic differentiation. We found that ADSCs treated with melatonin at a concentration of 100 µM had a higher viability compared to those treated at higher melatonin concentrations. Melatonin did not change the phenotype of ADSCs or induce apoptosis and it promoted the activity of some osteogenesis-related genes. We concluded that melatonin is safe, non-toxic to normal ADSCs in vitro, and can be used in regenerative medicine at low doses (100 μM) to improve cell viability without negatively affecting the osteogenic potential of these cells. Full article
(This article belongs to the Section Natural Products)
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Figure 1
<p>The influence of melatonin (<b>A</b>) and its inhibitor receptors (<b>B</b>) on ADSC viability. Each bar represents the mean percentage ± SD of the control cell viability (100%). (<b>A</b>) ADSC viability after treatment with melatonin at different concentrations: 0.1 μM, 1 μM, 10 μM, and 100 μM, expressed as a percent of CTRL. CTRL neg—cells treated with 1% of Triton X (ANOVA, post hoc Tukey, * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL, ^ <span class="html-italic">p</span> &lt; 0.05 vs. 1000 µM, n = 8). (<b>B</b>) Viability of ADSCs grown for 48 h in the presence of melatonin (MEL), melatonin with luzindole (MEL + LUZ), melatonin with 4-P-PDOT (MEL + 4-P-PDOT), luzindole (LUZ), and 4-P-PDOT. CTRL—untreated cells; CTRL neg—cells treated with 1% of Triton X (ANOVA, post hoc Tukey, mean ± SD, * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL, # <span class="html-italic">p</span> &lt; 0.05 vs. MEL, n = 6).</p>
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<p>Unchanged morphology of ADSCs after a 48 h exposure to melatonin (MEL), melatonin with luzindole (MEL + LUZ), and melatonin with 4-P-PDOT (MEL + 4-P-PDOT), as compared to the untreated cells (CTRL). Scale bars—30 µm (magn. 40×; magn. in the miniature: 100×).</p>
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<p>Expression of mesenchymal stem cell markers—CD73, CD90, and CD105—after a 48 h culture in the presence of melatonin (MEL), melatonin with luzindole (MEL + LUZ), melatonin with 4-P-PDOT (MEL + 4-P-PDOT), and in the control cells. (<b>A</b>) FACS histograms representative of CD73+, CD90+, and CD105+ ADSC cells. (<b>B</b>) Number of CD73+, CD90+, and CD105+ cells as a percentage of cultured ADSCs (ANOVA, post hoc Tukey, <span class="html-italic">p</span> &lt; 0.05, mean ± SD, n = 3).</p>
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<p>Detection of apoptotic or necrotic cells in cultures treated for 48 h with melatonin (MEL), melatonin with luzindole (MEL + LUZ), and melatonin with 4-P-PDOT (MEL + 4-P-PDOT). (<b>A</b>) FACS analyses representative of the experimental populations of ADSCs. (<b>B</b>) Mean percentage of live-, early-, or late-apoptotic and necrotic cells in cultured ADSC populations (* <span class="html-italic">p</span> &lt; 0.05 as compared to necrotic and apoptotic cells, ANOVA, post hoc Tukey, <span class="html-italic">p</span> &lt; 0.05, n = 3).</p>
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<p>Immunodetection of cleaved caspase-3 in ADSCs treated for 48 h with melatonin (MEL), melatonin with luzindole (MEL + LUZ), and melatonin with 4-P-PDOT (MEL + 4-P-PDOT), compared to untreated cells (CTRL). (<b>A</b>) Polyclonal primary antibody (1:400) and secondary antibody conjugated with fluorochrome Alexa Fluor 488 (1:1000) were used for cleaved caspase-3 (Asp175) visualized with FITC (green). Cell nuclei were visualized with DAPI (blue). Apoptotic ADSCs cultured in 2% DMSO served as the positive control (CTRL pos). In experimental groups: scale bars—15 µm, magn. 100×. In isotype controls: scale bars—40 µm, magn. 40×. (<b>B</b>) Mean fluorescence intensity (MFI) measured with ImageJ software v. 1.52a (ANOVA, post hoc Tukey, * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL, mean ± SD, n = 3).</p>
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<p>Flow cytometric analysis of cell cycle in ADSCs treated for 48 h with melatonin (MEL), melatonin with luzindole (MEL + LUZ), and melatonin with 4-P-PDOT (MEL + 4-P-PDOT), and in untreated (CTRL) cells. (<b>A</b>) FACS histograms representative of experimental populations of ADSCs in different phases of the cell cycle. (<b>B</b>) Mean percentage of ADSCs representing different phases of cell cycle in experimental cultures (ANOVA, post hoc Tukey, <span class="html-italic">p</span> &lt; 0.05, n = 3).</p>
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<p>Expression of <span class="html-italic">MTNR1A</span> and <span class="html-italic">MTNR1B</span> genes in ADSCs after a 48 h exposure to: melatonin (MEL), melatonin with luzindole (MEL + LUZ), melatonin with 4-P-PDOT (MEL + 4-P-PDOT), and in control (CTRL) cells. Kruskal–Wallis test with multiple comparisons, medians, and quartiles (* <span class="html-italic">p</span> &lt; 0.05 vs. CTRL; # <span class="html-italic">p</span> &lt; 0.05 vs. MEL, n = 6).</p>
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<p>Effect of melatonin on hydroxyapatite and calcium deposition during ADSC differentiation. (<b>A</b>) The hydroxyapatite and calcium deposition secreted by ADSCs after 7 days of differentiation with melatonin (MEL_O), melatonin with luzindole (MEL + LUZ_O), and melatonin with 4-P-PDOT (MEL + 4-P-PDOT_O), as well as a culture of untreated, differentiated (CTRL_O), and undifferentiated ADSCs (CTRL neg). The process of extracellular calcium deposition was assessed using staining with Alizarin red solution (red color) and the identification of hydroxyapatite with an Osteoimage Kit (green fluorescence). (<b>B</b>) Relative fluorescence of hydroxyapatite in examined groups (means ± SD, * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL_O, ANOVA, post hoc Tukey, <span class="html-italic">p</span> &lt; 0.05, means ± SD, n = 6). Scale bars—15 µm; magn. 100×.</p>
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<p>Expression of <span class="html-italic">BGLAP</span>, <span class="html-italic">SPP1</span>, and <span class="html-italic">RUNX2</span> genes in ADSCs after 7-day differentiation with melatonin (MEL_O), melatonin with luzindole (MEL + LUZ_O), melatonin with 4-P-PDOT (MEL + 4-P-PDOT_O), and in untreated cells (CTRL_O) (ANOVA, post hoc Tukey, <span class="html-italic">p</span> &lt; 0.05, means ± SD, n = 6, * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL_O, # <span class="html-italic">p</span> &lt; 0.05 vs. MEL_O).</p>
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<p>The concentrations of RUNX2 (<b>A</b>) and osteocalcin (<b>B</b>) in ADSCs after 7-day differentiation into osteoblasts. (<b>A</b>) * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL_O, # <span class="html-italic">p</span> &lt; 0.05 vs. MEL_O, n = 6. (<b>B</b>) * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL_O; # <span class="html-italic">p</span> &lt; 0.05 vs. MEL + LUZ_O, ANOVA, post hoc Tukey, <span class="html-italic">p</span> &lt; 0.05, means ± SD, n = 6.</p>
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<p>Visualization of RUNX2 (<b>A</b>) and osteocalcin (<b>B</b>) in differentiated ADSCs. (<b>A</b>) Monoclonal primary antibody (1:50) and secondary antibody conjugated with fluorochrome Alexa Fluor 488 (1:1000) were used for RUNX2 visualized with FITC (green). (<b>B</b>) Monoclonal primary antibody (1:500) and secondary antibody conjugated with fluorochrome Alexa Fluor 568 (1:1000) were used for OCN visualized with TRITC (red). Cell nuclei were visualized with DAPI (blue). Scale bars—15 µm, are representative for all images; magn. 100×.</p>
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12 pages, 2436 KiB  
Article
Gene–Diet Interactions: Viability of Lactoferrin-Fortified Yoghurt as an Element of Diet Therapy in Patients Predisposed to Overweight and Obesity
by Anna Jańczuk-Grabowska, Tomasz Czernecki and Aneta Brodziak
Foods 2023, 12(15), 2929; https://doi.org/10.3390/foods12152929 - 2 Aug 2023
Viewed by 1637
Abstract
Given the availability of molecular tools, population studies increasingly include the gen-diet interactions in their considerations. The use of these interactions allows for the obtaining of more uniform research groups. In practice, this translates into the possibility of reducing the size of the [...] Read more.
Given the availability of molecular tools, population studies increasingly include the gen-diet interactions in their considerations. The use of these interactions allows for the obtaining of more uniform research groups. In practice, this translates into the possibility of reducing the size of the research group while maintaining the precision of the research. The research results obtained in this way can be used to select certain ingredients and foods in a dietary intervention with a higher degree of personalisation. In both prophylaxis and dietary therapy of overweight and obesity, the proper selection of bioactive ingredients best suited to the given group of consumers is of key importance. Hence, the aim of the presented study was to assess the effectiveness of a dietary intervention with the use of lactoferrin (LF)-fortified yoghurt, in terms of the ability to regulate body weight and carbohydrate metabolism in individuals whose genomes contained single nucleotide polymorphisms that predisposed them to increased accumulation of fatty tissue and consequently overweight or obesity. A group of 137 participants (98 women and 37 men) of Polish origin were screened for the presence of four single nucleotide polymorphisms (rs993960—FTO gene, rs7903146—TCF7L2 gene, rs10830963—MTNR1B gene, and rs1121980—FTO gene). Subsequently, a group of 19 participants diagnosed with the presence of risk factors within said SNPs underwent a 21-day dietary intervention (crossover study) with the use of yoghurt fortified with lactoferrin (200 mg/day). The results of the study revealed a genetic difference between the Polish population and the European average, in terms of the SNPs analysed. The dietary intervention showed a statistically significantly higher efficiency in terms of body mass reduction (p = 0.000) and lowering the glycated haemoglobin ratio (HbA1c) (p = 0.000) when consuming specially prepared yoghurt containing lactoferrin, as compared to results registered for unfortified yoghurt. Given the above, yoghurt fortified with LF should be considered as a viable element of diet therapy in overweight and obese patients diagnosed with risk factors within the analysed polymorphisms. Full article
(This article belongs to the Section Food Nutrition)
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<p>Distribution of genetic variants in SNP rs9939609 in the studied population compared to the European population.</p>
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<p>Distribution of genetic variants in SNP rs1121980 in the studied population compared to the European population.</p>
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<p>Distribution of genetic variants in SNP rs7903146 in the studied population compared to the European population.</p>
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<p>Distribution of genetic variants in SNP rs10830963 in the studied population compared to the European population.</p>
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<p>Body weight loss of study participants in the 21/7 day and 7/21 day regimen. A, B —differences between the research groups within the sex; A, B—significant differences at <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Reduction of the concentration of HbA1c of study participants in the 21/7 day and 7/21 day regimen. A, B—differences between the research groups within the sex; A, B—significant differences at <span class="html-italic">p</span> ≤ 0.01.</p>
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13 pages, 302 KiB  
Article
Myocardial Infarction Susceptibility and the MTNR1B Polymorphisms
by Ivana Škrlec, Zrinka Biloglav, Jasminka Talapko, Snježana Džijan, Danijela Daus-Šebeđak and Vera Cesar
Int. J. Mol. Sci. 2023, 24(14), 11444; https://doi.org/10.3390/ijms241411444 - 14 Jul 2023
Cited by 2 | Viewed by 1415
Abstract
Melatonin is a circadian hormone with antioxidant properties that protects against myocardial ischemia-reperfusion injury. Genetic variations of the melatonin receptor 1B gene (MTNR1B) play an important role in the development of type 2 diabetes, a risk factor for cardiovascular diseases. Accordingly, [...] Read more.
Melatonin is a circadian hormone with antioxidant properties that protects against myocardial ischemia-reperfusion injury. Genetic variations of the melatonin receptor 1B gene (MTNR1B) play an important role in the development of type 2 diabetes, a risk factor for cardiovascular diseases. Accordingly, MTNR1B polymorphisms are crucial in numerous disorders of the cardiovascular system. Therefore, the aim of the present study was to investigate a possible association of MTNR1B polymorphisms with chronotype and susceptibility to myocardial infarction. The present case-control study included 199 patients with myocardial infarction (MI) (57% men) and 198 control participants (52% men) without previous cardiovascular diseases who underwent genotyping for the MTNR1B polymorphisms rs10830963, rs1387153, and rs4753426 from peripheral blood samples. Chronotype was determined using the Morningness-Eveningness Questionnaire (MEQ). As estimated by the chi-square test, no significant association was found in the distribution of alleles and genotypes between myocardial infarction patients and controls. In addition, there was no association between MTNR1B polymorphisms and chronotype in MI patients. As some previous studies have shown, the present negative results do not exclude the role of the MTNR1B polymorphisms studied in the development of myocardial infarction. Rather, they may indicate that MTNR1B polymorphisms are a minor risk factor for myocardial infarction. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
13 pages, 807 KiB  
Article
The Association between Dietary Iron Intake, SNP of the MTNR1B rs10830963, and Glucose Metabolism in Chinese Population
by Liping Shen, Zhengyuan Wang, Jiajie Zang, Hong Liu, Ye Lu, Xin He, Chunfeng Wu, Jin Su and Zhenni Zhu
Nutrients 2023, 15(8), 1986; https://doi.org/10.3390/nu15081986 - 20 Apr 2023
Cited by 1 | Viewed by 1355
Abstract
Type 2 diabetes is associated with both dietary iron intake and single-nucleotide polymorphism (SNP) of intronic rs10830963 in melatonin receptor 1B (MTNR1B); however, it is unclear whether they interact. The aim of this study was to examine the associations between dietary iron intake, [...] Read more.
Type 2 diabetes is associated with both dietary iron intake and single-nucleotide polymorphism (SNP) of intronic rs10830963 in melatonin receptor 1B (MTNR1B); however, it is unclear whether they interact. The aim of this study was to examine the associations between dietary iron intake, SNP of rs10830963, and glucose metabolism. Data were obtained from the Shanghai Diet and Health Survey (SDHS) during 2012–2018. Standardized questionnaires were carried out through face-to-face interviews. A 3-day 24 h dietary recall was used to evaluate dietary iron intake. Anthropometric and laboratory measurements were applied. Logistic regression and general line models were used to evaluate the association between dietary iron intake, SNP of the MTNR1B rs10830963, and glucose metabolism. In total, 2951 participants were included in this study. After adjusting for age, sex, region, years of education, physical activity level, intentional physical exercise, smoking status, alcohol use, and total energy, among G allele carriers, dietary iron intake was associated with a risk of elevated fasting glucose, higher fasting glucose, and higher HbA1c, while no significant results were observed among G allele non-carriers. The G allele of intronic rs10830963 in MTNR1B potentially exacerbated unfavorable glucose metabolism with the increasing dietary iron intake, and it was possibly a risk for glucose metabolism homeostasis in the Chinese population. Full article
(This article belongs to the Section Nutritional Epidemiology)
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<p>Flow chart of the study participants.</p>
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<p>Associations between dietary iron and risk of elevated fasting glucose among all participants stratified by G allele on the rs10830963 site of the MTNR1B gene. Data were presented as ORs for elevated fasting glucose according to the quartiles of dietary iron intake. The subgroup of G allele non-carriers in the lowest quartile of dietary iron intake (&lt;12.82 mg/day) was set to be the reference, meaning OR = 1.00. The other seven subgroups were compared with the reference subgroup.</p>
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23 pages, 753 KiB  
Review
Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes
by William L. Lowe
Int. J. Mol. Sci. 2023, 24(7), 6047; https://doi.org/10.3390/ijms24076047 - 23 Mar 2023
Cited by 5 | Viewed by 2651
Abstract
Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course [...] Read more.
Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26–30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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<p>Model for the relationship of maternal genetics, epigenetics, and environment in the risk for gestational diabetes and its long-term cardiometabolic outcomes.</p>
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15 pages, 2297 KiB  
Review
Molecular Mechanisms of the Melatonin Receptor Pathway Linking Circadian Rhythm to Type 2 Diabetes Mellitus
by An-Yu Xia, Hui Zhu, Zhi-Jia Zhao, Hong-Yi Liu, Peng-Hao Wang, Lin-Dan Ji and Jin Xu
Nutrients 2023, 15(6), 1406; https://doi.org/10.3390/nu15061406 - 15 Mar 2023
Cited by 7 | Viewed by 3490
Abstract
Night-shift work and sleep disorders are associated with type 2 diabetes (T2DM), and circadian rhythm disruption is intrinsically involved. Studies have identified several signaling pathways that separately link two melatonin receptors (MT1 and MT2) to insulin secretion and T2DM occurrence, [...] Read more.
Night-shift work and sleep disorders are associated with type 2 diabetes (T2DM), and circadian rhythm disruption is intrinsically involved. Studies have identified several signaling pathways that separately link two melatonin receptors (MT1 and MT2) to insulin secretion and T2DM occurrence, but a comprehensive explanation of the molecular mechanism to elucidate the association between these receptors to T2DM, reasonably and precisely, has been lacking. This review thoroughly explicates the signaling system, which consists of four important pathways, linking melatonin receptors MT1 or MT2 to insulin secretion. Then, the association of the circadian rhythm with MTNR1B transcription is extensively expounded. Finally, a concrete molecular and evolutionary mechanism underlying the macroscopic association between the circadian rhythm and T2DM is established. This review provides new insights into the pathology, treatment, and prevention of T2DM. Full article
(This article belongs to the Section Nutrition and Diabetes)
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<p>The regulation of melatonin synthesis in the dark. In the dark, melatonin synthesis in the pineal gland is regulated through successively transmitted nerve impulses. ① Astrocytes in the SCN are activated and release Glu, which interacts with NR2C, inducing the release of GABA. ② The sympathetic postsynaptic nerves release norepinephrine to activate AANAT, which promotes the synthesis of melatonin. AANAT: arylalkylamine-<span class="html-italic">N</span>-acetyltransferase; GABA: γ-aminobutyric acid; Glu: glutamate; NE: norepinephrine; NR2C: NMDA receptor 2 <span class="html-italic">C</span>-terminal; Trp: tryptophan. Both the red arrows in graph ① and black arrows in graph ② show the directions of signaling pathways, while the red upward arrows in graph ② represent concentration increases of each molecules.</p>
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<p>The regulation of melatonin receptors (MT<sub>1</sub>/MT<sub>2</sub>) on the secretion of insulin mediated via cAMP and cGMP pathways. Through MT<sub>1</sub> and MT<sub>2</sub> activation, the catalytic activity of AC is downregulated, leading to reduced activation of PKA. Then, PKA is inactivated in one of three pathways, the cAMP pathway, the cGMP pathway, and the K<sup>+</sup><sub>ATP</sub> channel, to regulate insulin secretion in combination. AC: adenylate cyclase; ATP: adenosine triphosphate; cADPR: cyclic ADP-ribose; cAMP: cyclic AMP; CaMKII: Ca<sup>2+</sup>/calmodulin-dependent protein kinase II; cGMP: cyclic GMP; CO: carbon monoxide; ER: endoplasmic reticulum; Gα<sub>i</sub>: the α subunit of the G protein; GTP: guanosine triphosphate; HO-2: heme oxygenase 2; nNOS: neuronal nitric oxide synthase; NAD<sup>+</sup>: nicotinamide adenine dinucleotide; NAADP: nicotinic acid adenine dinucleotide phosphate; NO: nitric oxide; PKA: protein kinase A; PKG: protein kinase G; sGC: soluble guanylyl cyclase; and SOCE: store-operated Ca<sup>2+</sup> entry.</p>
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<p>The regulatory effect of melatonin receptors (MT<sub>1</sub>, MT<sub>2</sub>) on the secretion of insulin via the IP<sub>3</sub> pathway. Through the PKC-dependent signaling pathway, the activation of MT<sub>1</sub> and MT<sub>2</sub> heterodimers ultimately causes Ca<sup>2+</sup> to traverse the plasma membrane, changing the level of insulin excreted. DAG: diacylglycerol; IP<sub>3</sub>: inositol-1,4,5-trisphosphate; PKC: protein kinase C; PLC: phospholipase C. PLC catalyzes PIP<sub>2</sub> transformation to DAG and IP<sub>3</sub>.</p>
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<p>The regulation of the melatonin receptor (MT<sub>2</sub>) to change insulin secretion via insulin gene transcription pathways. The binding of melatonin to MT<sub>2</sub> activates the downstream MAPK signaling pathway, which results in ERK1/2 activation. Then, through its interaction with YY1 and Foxo1 separately, ERK1/2 participates in the regulation of pre-proinsulin transcription and translation. Insulin also plays a positive role in its own secretion via the PI3K and PKB/Akt signaling pathways. ERK: extracellular signal-regulated kinase; Foxo1: a member of the large family of forkhead rhabdomyosarcoma transcription factors (FKHRs) [<a href="#B53-nutrients-15-01406" class="html-bibr">53</a>]; MEK: mitogen-activated protein kinase; PI3K: phosphatidylinositol-3-kinase; PKB/Akt: protein kinase B; Rb: retinoblastoma protein; YY1: Yin Yang 1.</p>
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<p>Molecular regulation of sunshine duration on the transcription of the <span class="html-italic">MTNR1B</span> gene. Specifically, rs10830963 allelic polymorphism show different MT<sub>2</sub> expression patterns in response to sunshine duration. (<b>A</b>) rs10830963G allele-containing <span class="html-italic">MTNR1B</span> and (<b>B</b>) rs10830963C allele-containing <span class="html-italic">MTNR1B</span>. The dash line indicates linkage disequilibrium between rs4753426C and rs10830963G.</p>
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14 pages, 3326 KiB  
Article
Melatonin Supplementation during the Late Gestational Stage Enhances Reproductive Performance of Sows by Regulating Fluid Shear Stress and Improving Placental Antioxidant Capacity
by Likai Wang, Laiqing Yan, Qi Han, Guangdong Li, Hao Wu, Xiao Ma, Mengmeng Zhao, Wenkui Ma, Pengyun Ji, Ran Zhang and Guoshi Liu
Antioxidants 2023, 12(3), 688; https://doi.org/10.3390/antiox12030688 - 10 Mar 2023
Cited by 4 | Viewed by 1960
Abstract
In this study, the effects of daily melatonin supplementation (2 mg/kg) at the late gestational stage on the reproductive performance of the sows have been investigated. This treatment potentially increased the litter size and birth survival rate and significantly increased the birth weight [...] Read more.
In this study, the effects of daily melatonin supplementation (2 mg/kg) at the late gestational stage on the reproductive performance of the sows have been investigated. This treatment potentially increased the litter size and birth survival rate and significantly increased the birth weight as well as the weaning weight and survival rate of piglets compared to the controls. The mechanistic studies have found that these beneficial effects of melatonin are not mediated by the alterations of reproductive hormones of estrogen and progesterone, nor did the glucose and lipid metabolisms, but they were the results of the reduced oxidative stress in placenta associated with melatonin supplementation. Indeed, the melatonergic system, including mRNAs and proteins of AANAT, MTNR1A and MTNR1B, has been identified in the placenta of the sows. The RNA sequencing of placental tissue and KEGG analysis showed that melatonin activated the placental tissue fluid shear stress pathway to stimulate the Nrf2 signaling pathway, which upregulated its several downstream antioxidant genes, including MGST1, GSTM3 and GSTA4, therefore, suppressing the placental oxidative stress. All these actions may be mediated by the melatonin receptor of MTNR1B. Full article
(This article belongs to the Special Issue Antioxidants in Husbandry Animal Production)
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<p>Melatonin level in blood and colostrum. (<b>A</b>) Blood melatonin levels at day 100 and 112 of gestation, respectively (<span class="html-italic">n</span> = 4 for per group). (<b>B</b>) Melatonin level in colostrum (<span class="html-italic">n</span> = 3 for per group). Data are presented as means ± SEM. * means <span class="html-italic">p</span> &lt; 0.05. ** means <span class="html-italic">p</span> &lt; 0.01. GD 100 = gestation day of 100, GD 112 = gestation day of 112, CON = control, MT = melatonin.</p>
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<p>Reproductive Performance of sows with melatonin supplementation. (<b>A</b>) The number of sows giving birth during the day and night (<span class="html-italic">n</span> = 6). (<b>B</b>) The average number of newborn piglets (<span class="html-italic">n</span> = 5 for CON, <span class="html-italic">n</span> = 6 for MT group). (<b>C</b>) The average number of born alive (<span class="html-italic">n</span> = 5 for CON, <span class="html-italic">n</span> = 6 for MT group). (<b>D</b>) Average birth weight of piglets (<span class="html-italic">n</span> = 55 for CON, <span class="html-italic">n</span> = 72 for MT group). (<b>E</b>) Average weaning survival rate (<span class="html-italic">n</span> = 5 for CON, <span class="html-italic">n</span> = 6 for MT group). (<b>F</b>) Average weaning weight of piglets (<span class="html-italic">n</span> = 30 for CON, <span class="html-italic">n</span> = 36 for MT group), to avoid the stress of all piglets during weighing and affecting their growth, only six piglets from each sow were randomly selected for weighing). Data are presented as means ± SEM. * <span class="html-italic">p</span> &lt; 0.05. ** <span class="html-italic">p</span> &lt; 0.01. CON = control, MT = melatonin.</p>
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<p>Effects of melatonin supplementation on blood hormone and other biochemical indices. (<b>A</b>) Prolactin concentration (GD100, <span class="html-italic">n</span> = 5, GD112, <span class="html-italic">n</span> = 3). (<b>B</b>) Progesterone concentration (GD100, <span class="html-italic">n</span> = 5, GD112, <span class="html-italic">n</span> = 3). (<b>C</b>) Estrogen concentration (GD100, <span class="html-italic">n</span> = 5, GD112, <span class="html-italic">n</span> = 3). (<b>D</b>) Cortisol concentration (GD100, <span class="html-italic">n</span> = 5, GD112, <span class="html-italic">n</span> = 3). (<b>E</b>) Glucose concentration (GD100, <span class="html-italic">n</span> = 5, GD112, <span class="html-italic">n</span> = 3). (<b>F</b>) Triglyceride concentration (GD100, <span class="html-italic">n</span> = 5, GD112, <span class="html-italic">n</span> = 3). Data are presented as means ± SEM. * <span class="html-italic">p</span> &lt; 0.05. GD 100 = gestation day of 100, GD 112 = gestation day of 112, CON = control, MT = melatonin.</p>
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<p>Detection of the melatonergic system in placental tissue of sows and effects of melatonin supplementation on it. (<b>A</b>) Location of MTNR1A, MTNR1B and AANAT in placental tissue. (<b>B</b>,<b>C</b>) The mRNA expression levels of MTNR1A and MTNR1B (<span class="html-italic">n</span> = 5). (<b>D</b>) The protein expression level of AANAT (<span class="html-italic">n</span> = 4). (<b>E</b>) The mRNA expression levels of AANAT (<span class="html-italic">n</span> = 5). Data are presented as means ± SEM. * <span class="html-italic">p</span> &lt; 0.05. CON = control, MT = melatonin.</p>
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<p>Effects of melatonin supplementation on the transcriptome of placental tissue. (<b>A</b>) Cluster analysis. (<b>B</b>) Expression difference analysis. (<b>C</b>) Analysis of biological processes in GO. (<b>D</b>) Analysis of cellular components in GO. (<b>E</b>) Analysis of molecular function in GO. (<b>F</b>) KEGG enrichment analysis.</p>
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<p>Effects of melatonin supplementation on the antioxidant capacity of placental tissue. (<b>A</b>) The mRNA expression levels of MGST1 (<span class="html-italic">n</span> = 5). (<b>B</b>) The mRNA expression levels of GSTM3 (<span class="html-italic">n</span> = 5). (<b>C</b>) The mRNA expression levels of GSTA4 (<span class="html-italic">n</span> = 5). (<b>D</b>) The mRNA expression levels of GSTA1 (<span class="html-italic">n</span> = 5). (<b>E</b>) The mRNA expression levels of SOD2 (<span class="html-italic">n</span> = 5). (<b>F</b>) MDA concentration in peripheral blood (<span class="html-italic">n</span> = 3). Data are presented as means ± SEM. * <span class="html-italic">p</span> &lt; 0.05. CON = control, MT = melatonin.</p>
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<p>Patterns of increase in birth weight and weaning weight by melatonin supplementation in late gestation of sows (GD 90–GD 114).</p>
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13 pages, 421 KiB  
Article
Analysis of MTNR1A Genetic Polymorphisms and Their Association with the Reproductive Performance Parameters in Two Mediterranean Sheep Breeds
by Asma Arjoune, Abrar B. Alsaleh, Safia A. Messaoudi, Hanen Chelbi, Refka Jelassi, Mourad Assidi, Taha Najar, Brahim Haddad and Marc-André Sirard
Animals 2023, 13(3), 448; https://doi.org/10.3390/ani13030448 - 28 Jan 2023
Cited by 5 | Viewed by 1932
Abstract
Sheep farming plays an important economic role, and it contributes to the livelihoods of many rural poor in several regions worldwide and particularly in Tunisia. Therefore, the steady improvement of ewes’ reproductive performance is a pressing need. The MTNR1A gene has been identified [...] Read more.
Sheep farming plays an important economic role, and it contributes to the livelihoods of many rural poor in several regions worldwide and particularly in Tunisia. Therefore, the steady improvement of ewes’ reproductive performance is a pressing need. The MTNR1A gene has been identified as an important candidate gene that plays a key role in sheep reproduction and its sexual inactivity. It is involved in the control of photoperiod-induced seasonality mediated by melatonin secretion. The aim of this study was to identify SNPs in the MTNR1A gene in two Tunisian breeds, Barbarine (B) and Queue Fine de l’Ouest (QFO). DNA extracted from the blood of 77 adult ewes was sequenced. Selected ewes were exposed to adult fertile rams. A total of 26 SNPs were detected; 15 SNPs in the promoter region and 11 SNPs in the exon II were observed in both (B) and (QFO) breeds. The SNP rs602330706 in exon II is a novel SNP detected for the first time only in the (B) breed. The SNPs rs430181568 and rs40738822721 (SNP18 and SNP20 in our study, respectively) were totally linked in this study and can be considered a single marker. DTL was associated with SNP18 and SNP20 in (B) ewes (p < 0.05); however, no significant difference was detected between the three genotypes (G/G, G/A, and A/A) at these two SNPs. Fertility rate and litter size parameters were not affected by SNP18 and SNP20. There was an association between these two polymorphisms and (B) lambs’ birth weights (p < 0.05). Furthermore, the ewes with the A/A genotype gave birth to lambs with a higher weight compared to the other two genotypes for this breed (p < 0.05). There was not an association between SNP 18 and SNP20 and (QFO) ewes’ reproductive parameters. These results might be considered in future sheep selection programs for reproductive genetic improvement. Full article
(This article belongs to the Special Issue Recent Advances on the Role of Melatonin in Animal Reproduction)
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<p>The linkage disequilibrium plot (<span class="html-italic">p</span> value) among all the SNPs in <span class="html-italic">MTNR1A</span> gene sequence found in our study.</p>
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Article
Aggregation of Genome-Wide Association Data from FinnGen and UK Biobank Replicates Multiple Risk Loci for Pregnancy Complications
by Anton I. Changalidis, Evgeniia M. Maksiutenko, Yury A. Barbitoff, Alexander A. Tkachenko, Elena S. Vashukova, Olga V. Pachuliia, Yulia A. Nasykhova and Andrey S. Glotov
Genes 2022, 13(12), 2255; https://doi.org/10.3390/genes13122255 - 30 Nov 2022
Cited by 4 | Viewed by 3467
Abstract
Complications endangering mother or fetus affect around one in seven pregnant women. Investigation of the genetic susceptibility to such diseases is of high importance for better understanding of the disease biology as well as for prediction of individual risk. In this study, we [...] Read more.
Complications endangering mother or fetus affect around one in seven pregnant women. Investigation of the genetic susceptibility to such diseases is of high importance for better understanding of the disease biology as well as for prediction of individual risk. In this study, we collected and analyzed GWAS summary statistics from the FinnGen cohort and UK Biobank for 24 pregnancy complications. In FinnGen, we identified 11 loci associated with pregnancy hypertension, excessive vomiting, and gestational diabetes. When UK Biobank and FinnGen data were combined, we discovered six loci reaching genome-wide significance in the meta-analysis. These include rs35954793 in FGF5 (p=6.1×109), rs10882398 in PLCE1 (p=8.9×109), and rs167479 in RGL3 (p=5.2×109) for pregnancy hypertension, rs10830963 in MTNR1B (p=4.5×1041) and rs36090025 in TCF7L2 (p=3.4×1015) for gestational diabetes, and rs2963457 in the EBF1 locus (p=6.5×109) for preterm birth. In addition to the identified genome-wide associations, we also replicated 14 out of 40 previously reported GWAS markers for pregnancy complications, including four more preeclampsia-related variants. Finally, annotation of the GWAS results identified a causal relationship between gene expression in the cervix and gestational hypertension, as well as both known and previously uncharacterized genetic correlations between pregnancy complications and other traits. These results suggest new prospects for research into the etiology and pathogenesis of pregnancy complications, as well as early risk prediction for these disorders. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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<p>Genome-wide association results for hypertension complicating pregnancy, childbirth, and the puerperium (<b>a</b>), gestational hypertension (<b>b</b>), excessive vomiting in pregnancy (<b>c</b>), and gestational diabetes (<b>d</b>) in the FinnGen data. Manhattan plots and quantile-quantile plots are shown. Significant loci and lead SNP genes are highlighted.</p>
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<p>Genome-wide meta-analysis results for hypertension complicating pregnancy, childbirth, and the puerperium (<b>a</b>), gestational diabetes (<b>b</b>), and preterm birth (<b>c</b>). Manhattan plots and quantile-quantile plots are shown. Significant loci and lead SNP genes are highlighted.</p>
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<p>Heatmaps showing: (<b>a</b>,<b>b</b>) Significant genetic correlations in the FG dataset for hypertension complicating pregnancy, childbirth, and the puerperium (HP), gestational hypertension (GH), excessive vomiting in pregnancy (EV), and gestational diabetes (GD): (<b>a</b>) supported by other studies and/or mechanistic evidence, (<b>b</b>) novel or not previously reported; (<b>c</b>) significant genetic correlations of HP, GD, and preterm birth (PTB) computed using UKB + FG meta-analyses collection. Star sign represents significant correlation in the Wald test after FDR correction. Correlation limits are set to (−1, 1).</p>
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